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Vijay Narayanan
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Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators


Feb 16, 2023
Malte J. Rasch, Charles Mackin, Manuel Le Gallo, An Chen, Andrea Fasoli, Frederic Odermatt, Ning Li, S. R. Nandakumar, Pritish Narayanan, Hsinyu Tsai, Geoffrey W. Burr, Abu Sebastian, Vijay Narayanan

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* 35 pages, 7 figures, 5 tables 
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In-memory Realization of In-situ Few-shot Continual Learning with a Dynamically Evolving Explicit Memory


Jul 14, 2022
Geethan Karunaratne, Michael Hersche, Jovin Langenegger, Giovanni Cherubini, Manuel Le Gallo-Bourdeau, Urs Egger, Kevin Brew, Sam Choi, INJO OK, Mary Claire Silvestre, Ning Li, Nicole Saulnier, Victor Chan, Ishtiaq Ahsan, Vijay Narayanan, Luca Benini, Abu Sebastian, Abbas Rahimi

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* Accepted at the European Solid-state Devices and Circuits Conference (ESSDERC), September 2022 
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Joint Coreset Construction and Quantization for Distributed Machine Learning


Apr 13, 2022
Hanlin Lu, Changchang Liu, Shiqiang Wang, Ting He, Vijay Narayanan, Kevin S. Chan, Stephen Pasteris

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A flexible and fast PyTorch toolkit for simulating training and inference on analog crossbar arrays


Apr 05, 2021
Malte J. Rasch, Diego Moreda, Tayfun Gokmen, Manuel Le Gallo, Fabio Carta, Cindy Goldberg, Kaoutar El Maghraoui, Abu Sebastian, Vijay Narayanan

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* Submitted to AICAS2021 
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Robust Coreset Construction for Distributed Machine Learning


Apr 11, 2019
Hanlin Lu, Ming-Ju Li, Ting He, Shiqiang Wang, Vijay Narayanan, Kevin S Chan

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A Quantitative Evaluation Framework for Missing Value Imputation Algorithms


Nov 10, 2013
Vinod Nair, Rahul Kidambi, Sundararajan Sellamanickam, S. Sathiya Keerthi, Johannes Gehrke, Vijay Narayanan

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* 9 pages 
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